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Rough set approach to incomplete information systems. (English) Zbl 0951.68548

Summary: We present rough set approach to reasoning in incomplete information systems. We propose reduction of knowledge that eliminates only that information, which is not essential from the point of view of classification or decision making. In our approach we make only one assumption about unknown values: the real value of a missing attribute is one from the attribute domain. However, we do not assume which one. We show how to find decision rules directly from such an incomplete decision table, which are as little non-deterministic as possible and have minimal number of conditions.

MSC:

68T30 Knowledge representation
03E72 Theory of fuzzy sets, etc.
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[1] Pawlak, Z., (Rough Sets: Theoretical Aspects of Reasoning about Data, vol. 9 (1991), Kluwer Academic Publishers: Kluwer Academic Publishers Dordrecht) · Zbl 0758.68054
[2] Chmielewski, M. R.; Grzymala-Busse, J. W.; Peterson, N. W.; Than, S., The rule induction system LERS - A version for personal computers, Found. Comput. Decision Sci., 18, 3/4, 181-212 (1993) · Zbl 0806.68089
[3] Slowinski, R.; Stefanowski, J., Rough classification in incomplete information systems, Math. Comput. Modelling, 12, 10/11, 1347-1357 (1989)
[4] Slowinski, R.; Stefanowski, J., Handling various types of uncertainty in the rough set approach, (Ziarko, W., Rough Sets Fuzzy Sets and Knowledge Discovery (RSKD ’93) (1994), Springer: Springer Berlin) · Zbl 0819.68042
[5] Kryszkiewicz, M., Knowledge Reduction in Information Systems, (Ph.D. Thesis (1994), Warsaw University of Technology)
[6] Pawlak, Z.; Skowron, A., A rough set approach to decision rules generation, (ICS Research Report 23/93 (1993), Warsaw University of Technology) · Zbl 0794.03045
[7] Skowron, A., Management of uncertainty in AI: A rough set approach, (ICS Research Report 46/93 (December 1993), Warsaw University of Technology) · Zbl 0939.68736
[8] Skowron, A.; Rauszer, C., The discernibility matrices and functions in information systems, (Slowinski, R., Intelligent Decision Support: Handbook of Applications and Advances of Rough Sets Theory (1992), Kluwer Academic Publisher: Kluwer Academic Publisher Dordrecht), 331-362
[9] Skowron, A.; Stepaniuk, J., Generalized approximation spaces, (Proceedings of the Third International Workshop on Rough Sets and Knowledge Discovery RSSC ’94. Proceedings of the Third International Workshop on Rough Sets and Knowledge Discovery RSSC ’94, San Jose, USA (1994)), 156-163
[10] Kryszkiewicz, M., Rules in incomplete information systems, (Proceedings from the Third Joint Conference on Information Sciences. Proceedings from the Third Joint Conference on Information Sciences, North Carolina, USA (2-5 March 1997)) · Zbl 0948.68214
[11] Kryszkiewicz, M., Generation of rules from incomplete information systems (25-27 June 1997), submitted to PKDD’97, Trondheim Norway
[12] Lipski, W. J., On semantic issues connected with incomplete information databases, ACM Trans. Databases Systems, 4, 262-296 (1979)
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